Bibliographic record
Abstract
Cataphors precede their antecedents, so they cannot be fully interpreted until those antecedents are encountered. Some researchers propose that cataphors trigger an active search during incremental processing in which the parser predictively posits potential antecedents in upcoming syntactic positions (Kazanina et al., Journal of Memory and Language, 56[3], 384-409, 2007). One characteristic of active search is that it is persistent: If a prediction is disconfirmed in an earlier position, the parser should iteratively search later positions until the predicted element is found. Previous research has assumed, but not established, that antecedent search is persistent. In four experiments in English and Norwegian, we test this hypothesis. Two sentence completion experiments show a strong off-line preference for coreference between a fronted cataphor and the first available argument position (the main subject). When the main subject cannot be the antecedent, participants posit the antecedent in the next closest position: object position. Two self-paced reading studies demonstrate that comprehenders actively expect the antecedent of a fronted cataphor to appear in the main clause subject position, and then successively in object position if the subject does not match the cataphor in gender. Our results therefore support the claim that antecedent search is active and persistent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".